Abstract
The activity of sensory neural populations carries information about the environment. This may be extracted from neural activity using different strategies. In the auditory brainstem, a recent theory proposes that sound location in the horizontal plane is decoded from the relative summed activity of two populations in each hemisphere, whereas earlier theories hypothesized that the location was decoded from the identity of the most active cells. We tested the performance of various decoders of neural responses in increasingly complex acoustical situations, including spectrum variations, noise, and sound diffraction. We demonstrate that there is insufficient information in the pooled activity of each hemisphere to estimate sound direction in a reliable way consistent with behavior, whereas robust estimates can be obtained from neural activity by taking into account the heterogeneous tuning of cells. These estimates can still be obtained when only contralateral neural responses are used, consistently with unilateral lesion studies. DOI: http://dx.doi.org/10.7554/eLife.01312.001.
Highlights
To localize sound sources in the horizontal plane, humans and many other species use submillisecond timing differences in the signals arriving at the two ears (Ashida and Carr, 2011)
We fitted a distribution to a set of measurements of best delays (BDs) and best frequency (BF) in 192 cells (Joris et al, 2006)
Initially proposed by Jeffress (1948), asserts that interaural time differences (ITDs) is represented in the activity pattern of neurons with heterogeneous tunings to ITD
Summary
To localize sound sources in the horizontal plane, humans and many other species use submillisecond timing differences in the signals arriving at the two ears (Ashida and Carr, 2011). ITD is represented by the identity of the most active cell in each frequency band, a labeled line code for sound location. This theory has proved successful in barn owls (Konishi, 2003), discrepancies have been observed in mammals. The smoothed peak decoder outperforms the hemispheric decoder at SNR below 10 dB, both for the guinea pig and the cat models. This decoder performs worst in quiet, it proves more robust than the hemispheric decoder. This is because BDs are more represented away from the center
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